Industrializing Proteomics to Transform the Future of Healthcare

Researchers are discovering a plethora of potential new biomarkers every year, each touted as the ‘next big thing’ that will help herald a new era of precision medicine. But so far, very few have made it into clinical practice. We find out how some proteomics laboratories are now tackling this bottleneck using a factory-type setup – to get more biomarkers into the clinic, faster.

“In many diseases, the medication given to the patient is often not effective – so we need to be able to stratify patients to give them the right drug, at the right dosage, at the right time,” says Professor Tony Whetton, Director of the Stoller Biomarker Discovery Centre at the University of Manchester.

But there is a giant hurdle in the way of this revolutionary new approach – known as precision medicine – becoming commonplace. To enable it to happen, doctors will need a battery of clinically robust biomarkers.

“The biomarker is the buzzword – it’s what allows us to distinguish between different states of the pathological process of disease,” explains Dr Alexandre Zougman, Team Leader in Clinical Proteomics at the University of Leeds. “For us, a biomarker is a protein – for others, it could be something else – a gene or a metabolite.”

“If you look into the literature there are literally thousands of papers about biomarkers, but in reality, you don’t see that many of them coming into the clinic. It has to change,” he adds.

Speeding up the proteomic biomarker pipeline

The Stoller Biomarker Discovery Centre in Manchester, which Whetton heads up, is the largest clinical biomarker facility in Europe. Its aim is not only to discover new biomarkers for diagnosis, prognosis and response to therapy – but also to validate and verify them for clinical use.

“Normally, the time-course for developing a new proteomics biomarker would be about 12 years or so. But by integrating all of the various aspects that are needed into a single centre we plan to cut down that time considerably,” says Whetton.

The team have set out to overcome all the potential pinch-points in the pipeline from lab to clinic as effectively as possible.

“Our first challenge is associating with a decent clinical study. The second is running the samples on mass spectrometers with the highest possible quality control you can achieve so that the data actually means something. And then you need to do informatics on extensive and deep datasets in order to turn it into information as swiftly as you possibly can,” explains Whetton.

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A proteomics factory

Biological relevance for precision medicine depends on having statistically relevant numbers of samples, and one way of tackling this is by using larger and larger sample sets.

“What we’ve done is industrialize the proteomics so that we can turn out digitized maps on sample after sample very swiftly,” says Whetton.

“Ordinarily, a proteomics lab might have one or two mass-spectrometers – but we’ve got 13 machines that can pump samples through the pipeline very effectively. Quality control is of a high level – and we’ve got a lot of high-end computing power so that we can process the data in a matter of seconds or minutes, whereas other labs may take hours,” he adds.

Moving biomarkers from the lab to the clinic

Importantly, the team are then able to contextualize their proteomics data with patients’ electronic healthcare records. And as the whole lab is built around good clinical practice, everything is in place to enable new biomarkers to move into the clinic as swiftly as possible.

Although there are a variety of different diseases where new clinical biomarkers may be helpful, the centre is currently focussing on inflammatory diseases and cancer.

“For example, we’ve been looking for markers of risk in ovarian and lung cancer and have had some successes,” says Whetton.

In other diseases, including rheumatoid arthritis, they are seeking to identify new biomarkers that can help determine whether someone is responding to a particular treatment.

Advances in proteomics technology

A key enabler for this new factory-like approach has been a coming-of-age for mass spectrometry coupled with liquid chromatography (LC-MS) alongside better data-acquisition methods.

Mark Cafazzo, Director, Global Academic & Applied Markets Business at SCIEX, explains: “Over the last few years, we have seen a step-change in the speed and sensitivity and also the dynamic range of these instruments to be able to acquire enough data that can also show you a measurement on the very low-abundance protein in the presence of high-abundance proteins.”

“And new methods of acquiring the data are enabling labs to run more and more samples and get a reproducible quantitative result across the sample set for every protein that they’re looking for,” he adds.

But despite recent advancements in technology, antibody-based assays still remain very much at the fore when it comes down to the pathology. However, there is hope that mass spectrometry platforms could become a fixture of pathology labs in the future.

“We also employ two professors of pathology to try and develop new tests that can actually get used as opposed to just being a technique or a technology that doesn’t impact on the clinic,” says Whetton.

Next-generation bioinformatics

The next big challenge will be to find ways to handle the increasingly large datasets – and also finding ways to integrate the various ‘omics data to tie it all together at the biological level.

Cafazzo explains: “If the study is designed right and you can get RNA-Seq, proteomics and metabolomics results on the same set of samples then you have a much more powerful, very multi-dimensional set of data to play with to try and tease out the most useful markers.”

But the informatics solutions needed to actually do that are still in their infancy, with bigger advances necessary to manage those very rich sets of data.

“Clusters and arrays of hardware in a local site is one way to address it. Or another is to put your data into a cloud solution and to make use of a number of more powerful technology software applications,” says Cafazzo.

Unlocking the benefits of precision medicine

The future looks bright for clinical proteomics, particularly with the added power of industrialized proteomics that will help to propel more biomarkers into the clinic. Unlocking the plethora of benefits promised by precision medicine relies on its success.

Zougman sums up: “If you can find a molecule that’s either a prognostic or a diagnostic tool in different diseases that’s just great – it’s great for patient management, for the disease outcome, and for the healthcare system economically.”

Once the preserve of big pharma, high-throughput screening and the data it has produced is now widely available. Together with advances in artificial intelligence, it is providing broad opportunities in drug discovery.